PAM50 gene expression subtypes represent a cornerstone in molecular classification of breast cancer and are included in risk prediction models to guide therapy. We aimed to illustrate the impact of included genes and biological processes on subtyping while considering a tumor’s underlying clinical subgroup defined by ER, PR and HER2 status. To do this we used a population-representative and clinically annotated primary breast tumor cohort of 6233 samples profiled by RNA sequencing and applied a perturbation strategy of excluding co-expressed genes (gene sets). We demonstrate how PAM50 nearest centroid classification depends on biological processes present across, but also within, ER/PR/HER2 subgroups and PAM50 subtypes themselves. Our analysis highlights several key aspects of PAM50 classification. Firstly, we observed a tight connection between a tumor’s nearest and second nearest PAM50 centroid. Additionally, we show that second-best subtype is associated with overall survival in ER-positive, HER2-negative, and node negative disease. We also note that ERBB2 has little impact on PAM50 classification in HER2-positive disease regardless of ER-status, and that the Basal subtype is highly stable in contrast to the Normal subtype. Improved consciousness of the commonly used PAM50 subtyping scheme will aid in our understanding and interpretation of breast tumors that have seemingly conflicting PAM50 classification when compared to clinical biomarkers. Finally, our study adds further support in challenging the common misconception that PAM50 subtypes are distinct classes by illustrating that PAM50 subtypes in tumors represent a continuum that may have clinical implications.

Introduction: Cancer patients (pts) suffer from a significant amount of psychosocial distress related to tumor disease itself or straining treatments. Despite recommendations how to screen for and to deal with psychosocial distress in cancer pts, data about implementation of psycho-oncological interventions (poi) in outpatient settings of cancer pts is scarce. Aim of this study was to identify outpatients with cancer in need of poi and to evaluate different assessment instruments. Methods: N=200 outpatients with haemato-/oncological malignancies were interviewed between October 2015 and December 2017 at the University Hospital Mannheim using the Basic Documentation for Psycho-Oncology (PO-Bado) and the Hornheider Screening Instrument (HSI) – both clinician-administered assessment tools – followed by descriptive, univariate and agreement analysis. Results: N=61 cancer pts (31%) were identified to be in need for poi considering the results of both questionnaires. The number of identified patients in need of poi was lower when analyzing the results of the PO-Bado (n=42, 21%) and the HSI (n=39, 20%) separately. The degree of agreement the results of PO-Bado and HSI was low (kappa=0.3655). Several factors like gender, age and diagnosis were identified to have significant impact on the need for poi (p≤0.05). Discussion/Conclusion: Our study underlines, that different screening instruments for psychosocial distress may identify disparate populations of cancer pts. The study data also revealed significant characteristics that might be associated with elevated levels of psychosocial distress and a clear indication for poi. However, further analyses on larger populations of cancer pts are needed to provide information how to transfer positive screening to poi in clinical routine.

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